The purpose of this study was to compare the heart rates of dogs presenting with spontaneous atrial fibrillation (AF) by a surface electrocardiogram (ECG) and a 24 hour ambulatory ECG (Holter recording) in order to determine if there was a difference between these two diagnostic tests. Seven dogs with clinically stable, spontaneous AF were evaluated with a 6 lead surface ECG (MAC 5000, GE® Milwaukee) and a Holter monitor (Monitor device: LifecardCE Delmar Reynolds Medical, Holter analysis:Aria Holter software). Statistical analyses, including t-tests and linear regression models, were performed using Stata® data-analysis and statistical software. When heart rates (bpm) determined by both diagnostic testing methods were compared individually and among all of the dogs, no statistically significant differences were found. Complete data for analysis were available in 4 of the 7 dogs. This study demonstrates that despite the potential superiority of Holter monitoring relative to the surface ECG for the diagnosis of cardiac arrhythmias, average heart rates were not statistically different in these 4 dogs with controlled AF. Therefore, the average HR determined by surface ECG in the hospital may be as reliable as the average HR determined by Holter monitoring in dogs with well controlled spontaneous AF.

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice, occurring in 1% of the adult population of North America. Although AF does not typically lead to risk of immediate mortality, it is a potent risk factor for ischemic stroke. When left untreated AF reduces quality of life, functional status, cardiac performance and is associated with higher medical costs and an increased risk of death. Catheter ablation is a commonly used treatment method for those who suffer from drugrefractory AF. Prior to ablation, intra-cardiac mapping can be used to determine the activation sequence of cardiac tissue, which may be useful in deciding where to place ablation lesions. However, the electrical potential that is recorded during mapping is not a direct reflection of the current density across the tissue because the potential recorded at each point above the heart tissue is influenced by every cell in the tissue. This causes the recorded potential to be a blurred version of the true tissue current density. The potential that is observed can be described as the convolution of the true current density with a point spread function. Accordingly, deconvolution can, in principle, be used in order to improve the resolution of potential maps. However, because the number of electrodes which can be deployed transvenously is limited by practical restrictions, the recorded potential field is a sparsely sampled version of the actual potential field. Further, an electrode array cannot sample over the entire atrial surface, so the potential map that is observed is a truncated version of the global electrical activity. Here, we investigate the effects of electrode sampling density and edge extension on the ability of deconvolution to improve the resolution of measured electrical potentials within the atria of the heart. In particular, we identify the density of sensing electrodes that are required to allow deconvolution to provide improved estimation of the true current density when compared to the observed potential field.

In my thesis, in the theoretical part I deal with atrial fibrillation. I also deal with management of atrial fibrillation treatment. In the paper I explain the basic principles of pharmaco-economic evaluation in the Czech Republic, on the basis of which laws these pharmacological interventions are evaluated and who are in the Czech Republic. In the work I present cost breakdown and what are the most commonly used pharmaco-economic analyzes. In the practical part I will apply the theoretical knowledge. I have developed cost utility analysis based on available clinical evidence - randomized clinical trials ARISTOTLE (Granger, 2011), RE-LY (Connolly, 2009), ROCKET AF (Patel, 2011). I made an indirect comparison of the total benefits of NOACs. In the baseline scenario, I have calculated QALY to evaluate the benefits of effectiveness, safety and reduction of mortality. I have also dealt with a bleeding-related scenario. The ICER's greatest contribution to the public healthcare system has shown the active substance apixaban in both scenarios. I added the results and confirmed the clinical results of a recent, robust, retrospective study by Mayo Clinic (Yao, 2016).

Atrial fibrillation is the most frequent clinically significant arrhythmia. Its occurrence in adult population was previously reported to be 0.4 %, currently it is more or less 0.95 %. In industrial countries the population of patients with ischemic heart disease is increasing; with progress in therapy of such patients the number of individuals with heart disease has increased. Increasing prevalence of atrial fibrillation, which occurs frequently with such diseases, is also expected. Concurrence with atrial flutter, atrial macroreetnry arrhythmia is relatively frequent. Both arrhythmias may alternate in a patent or change from one to another. Efforts with medication therapies were not sufficiently successful in the past. New products have been sought all the time – the products which would have influence on the atrial muscle and have no influence on ventricular myocardium, have no side effects and no proarrhythmogenic potential. Simultaneously, ways of non-pharmacological treatment have been sought. The non-pharmacological methods are prevailing currently since pharmaceutical products fail and have irregular effect. The category of non-pharmacological treatment includes cardio-stimulating methods and ablation techniques. Accordingly, there were no sufficiently sophisticated methods of evaluating of arrhythmia occurrence after ablation procedures. The development of efficient detection, processing and evaluation of heart activity proceeds to long-term monitoring of heart signals using an implantable heart monitor. The latest model of implantable heart monitor has been introduced in clinical practice; it is particularly intended for diagnostics of atrial arrhythmias. The above-mentioned implant bears trade name REVEALŽ XT, produced by the MEDTRONIC Company. This thesis elaborates comprehensively the issue of implantable heart monitors of the latest generation which are specially intent on diagnostics of atrial arrhythmias. It summarizes data that was collected as a part of two world-wide multicentre studies EPECT and VISIT. In this thesis I analyze data obtained at the centre of acute cardiology hospital Na Homolce. The data population offers a comprehensive view of potentials of subcutaneous heart monitors from the pre-implanting phase to one-year follow-up of detection properties and classifications of heart arrhythmias with a strong emphasis on an analysis of atrial tachyarrhythmias. Based on thus analyzed data the following conclusion can be made: The implantable heart monitor REVEALŽ XT is suitable for clinical applications of long-term monitoring of heart rhythm both in the area of ventricular and atrial arrhythmias.

Global rise in life expectancy has resulted in an increased demand for affordable healthcare and monitoring services. The advent of miniature and low–power sensor technologies coupled with the emergence of the Internet–of–Things has paved the way towards affordable health monitoring tools in wearable platforms. However, ensuring power–efficient operation, data accuracy and user comfort are critical for such wearable systems. This thesis focuses on the development of accurate and computationally efficient algorithms and low–cost, unobtrusive devices with potential predictive capability for monitoring mobility and cardiac health in a wearable platform. A three–stage complementary filter–based approach is developed to realize a computationally efficient method to estimate sensor orientation in real–time. A gradient descent–based approach is used to estimate the gyroscope integration drift, which is subsequently subtracted from the integrated gyroscope data to get the sensor orientation. This predominantly gyroscope–based orientation estimation approach is least affected by external acceleration and magnetic disturbances. A two–stage complementary filter–based efficient sensor fusion algorithm is developed for real–time monitoring of lower–limb joints that estimates the IMU inclinations in the first stage and uses a gradient descent–based approach in the second stage to estimate the joint angles. The proposed method estimates joint angles primarily from the gyroscope measurements without incorporating the magnetic field measurement, rendering the estimated angles least affected by any external acceleration and insensitive to magnetic disturbances. An IMU–based simple, low–cost and computationally efficient gait–analyzer is developed to track the course of an individual's gait health in a continuous fashion. Continuous monitoring of gait patterns can potentially enable detecting musculoskeletal or neurodegenerative diseases at the early onset. The proposed gait analyzer identifies an anomalous gait with moderate to high accuracy by evaluating the gait features with respect to the baseline clusters corresponding to an individual’s healthy peer group. The adoption of a computationally efficient signal analysis technique renders the analyzer suitable for systems with limited processing capabilities. A flexible dry capacitive electrode and a wireless ECG monitoring system with automatic anomaly detection capability are developed. The flexible capacitive electrode reduces motion artifacts and enables sensing bio–potential over a dielectric material such as cotton cloth. The virtual ground of the electrode allows for obtaining single–lead ECG using two electrodes only. ECG measurements obtained over different types of textile materials and in presence of body movements show comparable performance to other reported ECG monitoring systems. An algorithm is developed separately as a potential extension of the software to realize automatic identification of Atrial Fibrillation from short single–lead ECGs. The association between human gait and cardiac activities is studied. The gait is measured using wearable IMUs and the cardiac activity is measured with a single–lead handheld ECG monitor. Some key cardiac parameters, such as heart rate and heart rate variability and physical parameters, such as age and BMI show good association with gait asymmetry and gait variation. These associations between gait and heart can be useful in realizing low–cost in–home personal monitoring tool for early detecting CVD–related changes in gait features before the CVD symptoms are manifested. / Thesis / Doctor of Philosophy (PhD) / Wearable health monitoring systems can be a viable solution to meet the increased demand for affordable healthcare and monitoring services. However, such systems need to be energy–efficient, accurate and ergonomic to enable long–term monitoring of health reliably while preserving user comfort. In this thesis, we develop efficient algorithms to obtain real–time estimates of on–body sensors' orientation, gait parameters such as stride length, and gait velocity and lower–limb joint angles. Furthermore, we develop a simple, low–cost and computationally efficient gait–analyzer using miniature and low–power inertial motion units to track the health of human gait in a continuous fashion. In addition, we design flexible, dry capacitive electrodes and use them to develop a portable single–lead electrocardiogram (ECG) device. The flexible design ensures better conformity of the electrode to the skin, resulting in better signal quality. The capacitive nature allows for obtaining ECG signals over insulating materials such as cloth, thereby potentially enabling a comfortable means of long–term cardiac health monitoring at home. Besides, we implement an automatic anomaly detection algorithm that detects Atrial Fibrillation with good accuracy from short single–lead ECGs. Finally, we investigate the association between gait and cardiac activities. We observe that some important cardiac signs, such as heart rate and heart rate variability and physical parameters, such as age and BMI show good association with gait asymmetry and gait variation.